Method and system for identifying people who are likely to have a successful relationship

ABSTRACT

The functions and operations of a matching service are disclosed. This includes approximating the satisfaction that a user of the matching service has in the relationships that the user forms with others and identifying candidates for a relationship with the user based on the approximated satisfaction. This also includes approximating the satisfaction that the user will have in a relationship with a particular candidate. The matching service also identifies two parties for a relationship. The matching service makes available a plurality of communication levels at which the parties can communicate. Each communication level allows the parties to exchange information in a different format. The parties are permitted to exchange information at one of the communication levels.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This patent application discloses subject matter related to the subjectmatter contained in the U.S. patent application entitled “Method andSystem for Identifying People Who are Likely to Have a SuccessfulRelationship,” Ser. No. 09/635,889, filed on Aug. 10, 2000, and isincorporated by reference herein. This application is a continuation ofU.S. patent application Ser. No. 09/636,010, filed Aug. 10, 2000 nowU.S. Pat. No. 6,735,568.

BACKGROUND

1. Field of the Invention

The invention relates generally to operation of a matching service.Specifically, the invention relates to identifying and providingcommunication between people who are likely to have a successfulrelationship.

2. Background of the Invention

A matching service attempts to identify and bring together two or morepeople that the matching service believes may have a successfulrelationship. Many matching services identify matches by techniques thatfind people with common personalities, interests and/or beliefs.However, these matching techniques often do not account for the largenumber of variables that can determine whether a relationship issuccessful. Research has shown that the success of human relationshipsdepends on complex interactions between a large number of variablesincluding, but not limited to, personality, socioeconomic status,religion, appearance, ethnic background, energy level, education,interests and appearance. The large number of variables involved indetermining relationship success has made predicting the success of arelationship to be very unreliable. Accordingly, matching services areunable to reliably predict relationship success and their clients areoften disappointed with the results of their matches. As a result, thereis a need for a method of matching people that accounts for thecomplexity of the relationships between the variables that determinerelationship success.

After identifying candidates for a match, many matching services allowthe candidates to communicate by telephone or by e-mail. Many people arenot comfortable communicating with a new person in such an immediatelyopen format. As a result, many people would be comfortable with a moregradual and less personal introduction to new people. Accordingly, thereis a need for providing communication between matched candidates that iscomfortable to the candidates.

SUMMARY OF THE INVENTION

The invention relates to the functions and operation of a matchingservice. The invention, embodied as a method, includes approximating thesatisfaction that a user of the matching service has in therelationships that the user forms with others, and identifyingcandidates for a relationship with the user based on the approximatedsatisfaction. The method also includes approximating the satisfactionthat the user will have in a relationship with a particular candidate.

The method can also include classifying the user based on theapproximated satisfaction that the user will have in the relationshipsthat user forms with others. Candidates for matching with the user areidentified based on the classification of the user. The satisfactionthat the user is likely to have in a relationship with each of theidentified candidates is determined in order to identify the one or morecandidates with whom the user is most likely to have a successfulrelationship.

Another method for operating a matching service according to thisinvention includes receiving a plurality of surveys completed bydifferent users. Each survey includes a plurality of inquiries intomatters that are relevant to formation of relationships with otherpeople. At least a portion of the inquiries have answers that areassociated with a number. The method also includes using answers whichthe individuals provide to the inquiries in a factor analysis toidentify a plurality of factors. These factors are used to generate anindividual satisfaction estimator.

In one embodiment, the invention also includes identifying the factorsthat most highly predict satisfaction in a relationship.

Still another embodiment of the invention includes inputting into aneural network information provided by a user of the matching serviceand receiving from the neural network a list of one or more candidatesthat the neural network has determined will be successful in arelationship with the individual.

Yet another embodiment of the invention includes identifying two partiesfor a relationship and providing a plurality of communication levels.Each communication level allows the parties to exchange information in adifferent format. The invention also includes allowing the parties toexchange information at one of the communication levels.

One example of a communication level allows the parties to exchangeanswer to one or more closed-ended questions written by the matchingservice. Another example of a communication level allows exchange ofopen-ended questions written by the matching service. Yet anotherexample of a communication level allows exchange of items selected froma list created by the matching service.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for matching a user of a matching servicewith one or more candidates selected from among a pool of candidates.

FIG. 2 illustrates an example of a survey that is answered by numerousindividuals.

FIG. 3 illustrates the structure and contents of an empirical databasegenerated from the answers to the survey illustrated in FIG. 2.

FIG. 4 is an example of a correlation matrix that shows the degrees ofcorrelation between entries in the empirical database.

FIG. 5 illustrates factors as a function of the answers to one or moreinquiries on a survey.

FIG. 6 illustrates the structure and contents of a factor value databasethat lists the value of the factors for particular people.

FIG. 7 illustrates a linear regression performed on individualsatisfaction index data plotted versus the value of a particular factorfor the men listed in the factor value database.

FIG. 8 illustrates an example of a couple database which lists thedifference in the value of particular factors between the members of acouple.

FIG. 9 illustrates an individual satisfaction index plotted versus thevalue of the differential factor labeled ΔF₁

FIG. 10 illustrates the invention embodied as a method of operating amatching service.

FIG. 11 illustrates the invention embodied as a method of preparingempirical data in preparation for matching a user with one or morecandidates.

FIG. 12 illustrates the invention embodied as a method for using theprepared empirical data to match a user of the matching service with oneor more candidates.

FIG. 13 illustrates the invention embodied as a method of providingcommunication between the user of the service and the one or morecandidates.

FIG. 14 illustrates a supervised backpropogated neural network.

DETAILED DESCRIPTION

The invention relates to the functions and operation of a matchingservice. The matching service employs empirical data to identify andselect one or more candidates for a relationship with a user of theservice. When the user and one of the selected candidates wish tocommunicate, the matching service allows them to communicate at aplurality of communication levels. Each of the communication levelsallows the parties to exchange information in a different format.Examples of exchanging information at different communication levelsinclude exchanging answers to open-ended questions provided by thematching service, exchanging items selected from a list provided by thematching service, exchanging answers to open-ended questions provided bythe matching service and exchanging questions and answers written by theuser and/or the candidate.

In one embodiment of the invention there is no sequence assigned to thecommunication levels and the parties agree on which communication levelthey will communicate. As a result, people who are uncomfortable meetingsomeone in a very open format can choose a communication level with amore closed format such as one for exchanging closed-ended-questions.

In another embodiment of the invention, the matching service requiresthat the parties advance through a particular sequence or hierarchy ofcommunication levels. The matching service can sequence thecommunication levels to ensure a slow introduction of the two parties.Additionally, the subject matter of the communications can be controlledto limit the exchange of more personal information to latercommunication levels. The service starts the parties, the user and thecandidate, communicating at a particular communication level. In oneembodiment, the matching service controls when the parties advance fromone communication level to another. In another embodiment, the partiesare able to select when they will advance from one communication levelto the next level.

The matching service can facilitate each exchange of information byreceiving a portion of the communication from one party and thenforwarding the communication to the other party. The matching servicecan modify the communication so the identity of the sending party isconcealed. As a result, the communication between the parties remainsanonymous.

The identification and selection of particular candidates for arelationship with a user is based on empirical data about people and thesatisfaction these people have in their relationships. The matchingservice prepares the empirical data for use in matching people. The datapreparation can include generation of an individual satisfactionestimator and a couple satisfaction estimator.

The individual satisfaction estimator and a couple satisfactionestimator are used to match people. A user of the matching servicecompletes a survey to provide data to the matching service. The user'sdata is compared to an individual satisfaction estimator to approximatethe satisfaction the user has in his/her relationships with others.Candidates for matching with the user are identified based on theresults. For instance, the candidates have results which are similar tothe user to reduce matches between people who are likely to haveconflicting relationships.

One of the identified candidates is then selected. Data for the user anddata for the selected candidate is compared to approximate thesatisfaction that the user would have in a relationship with thecandidate. This is repeated for each of the identified candidates. Theresults are studied to identify the candidate and user combinations thatwould result in the most satisfaction. The user and the identifiedcandidates are then given the option of communicating with one another.

As described above, the approximate individual satisfaction index andthe couple satisfaction index are generated from empirical data. Theempirical data is generated from surveys completed by differentindividuals. Each survey includes a plurality of inquiries into matterswhich are relevant to each individual in forming relationships withother people. The inquiries can have numerical answers. These answersare used in a factor analysis to identify factors that are each afunction of one or more correlated inquiries. These factors are used inthe generation of the individual satisfaction estimator and the couplesatisfaction estimator. Because the factors are a function of severalinquiries, the use of the factors reduces the number of variablesconsidered when generating the approximate individual satisfaction indexand the couple satisfaction index. However, the complexity of therelationships between the variables (question answers) is retained inthe results because each of the variables are taken into considerationwhen generating the factors.

In one embodiment of the invention, a matching service uses the methodstaught in this specification to train a neural network. Training theneural network allows the matching service to take advantage of a neuralnetwork's ability to resolve problems in the presence of noisy andcomplex data. Additionally, the matching service can take advantage ofthe neural network to learn to improve the quality of the matchingresults.

FIG. 1 illustrates an embodiment of a system 10 for matching people whoare interested in establishing a relationship with other people. Thesystem 10 includes a network 12 providing communication between amatching service 14 and one or more remote units 16. The matchingservice 14 can include one or more processing units for communicatingwith the remote units 16. The processing units include electronics forperforming the methods and functions described in this application. Inone embodiment, the processing units include a neural network. Suitableremote units 16 include, but are not limited to, desktop personalcomputer, workstation, telephone, cellular telephone, personal digitalassistant (PDA), laptop, or any other device capable of interfacing witha communications network. Suitable networks 12 for communication betweenthe server and the remote units 16 include, but are not limited to, theInternet, an intranet, an extranet, a virtual private network (VPN) andnon-TCP/IP based networks 12.

A user of a remote unit 16 and the matching service 14 can communicateas shown by the arrow labeled A. Examples of communications includeexchange of electronic mail, web pages and answers to inquiries on webpages. The user of the remote unit 16 can also communicate with the userof another remote unit 16 as indicated by the arrow labeled B. Thematching service provides the communication by receiving thecommunication from one user and providing the communication to anotheruser. The matching service 14 can modify the communication from one userto another user. For instance, the matching service. 14 can change theuser's real name on an e-mail to a username so the sending user'sidentity is protected. The username can be assigned by the matchingservice 14 when the user signs up for the service or can be selected bythe user when the user signs up for the matching service 14. One usercan also communicate directly with another user as shown by the arrowlabeled C. This direct communication can occur after the users exchangee-mail addresses or phone numbers during a communication through thematching service 14. Alternatively, one user can request that thematching service 14 provide another user with his/her directcommunication information, i.e. e-mail address. The methods described inthe present invention can be performed using only the communicationsillustrated by the arrows labeled A, B and C. However, other forms ofcommunication can be used including normal mail services, phone callsand directly visiting the matching service.

The matching service 14 employs a data preparation stage, a matchingstage and a communications stage. During the data preparation stage,empirical data is manipulated in preparation for the matching stage. Theempirical data is used to match one or more candidates with a user inthe matching stage. At the communication stage, communication isachieved between the user and one or more of the users. Thecommunication can occur in one or more communication stages which areselected by the user and the candidate.

The matching service 14 employs empirical data during the datapreparation stage. The empirical data is generated from answers tosurveys such as the survey 20 illustrated in FIG. 2. The survey 20 asksa series of inquiries 22 that can be numerically answered. For instance,the inquiry “Do you like to go camping” is followed by a series ofnumbers arranged in a scale. The user provides an answer somewhere alongthe scale based on their preference for the activity. For instance, a“1” can indicate that the user enjoys camping while a “5” indicates thatthe user does not enjoy camping. Because the answer to each questionvaries from user to user, each inquiry and the associated answers areoften referred to as variables.

Surveys 20 can be completed for the purpose of generating enough datafor the matching service to make reliable matches. For instance, a largenumber of persons can be enlisted to fill out the surveys 20. Theseanswers can then be used to construct an empirical database that can beused in the method of matching persons. However, these people who fillout these surveys need not become candidates for the service to matchwith others. As will become more apparent from the following discussion,the empirical database preferably should include data from both membersof existing couples or previously existing couples. As a result, peopleselected to fill out surveys for the purpose of building an empiricaldatabase may be couples and may even be married.

The survey 20 can also be completed by means of a remote unit 16 withaccess to the matching service 14. The survey can be made available tothe user in the form of one or more web pages after the user hasregistered for use of the matching service. After submitting thecompleted survey to the matching service, the user can request a list ofpotentially matching candidates from the matching service. The user canalso request to become a candidate for matches with other users. Ineither case, the survey answers provided by the user are stored in theempirical database.

The survey and/or the registration process can also request that theuser submit preliminary information. Preliminary information isinformation that is provided to a user and a candidate to help themdetermine whether they would like to initiate communication with theother party. The information which is provided can be entirely up to theuser although the matching service can make suggestions aboutinformation which has been successful at eliciting responses. Thepreliminary information can include the user's appearance, interests,height, weight, location, age, picture, religion, business, etc. Theuser can also have the option of writing a short blurb abouthimself/herself.

The survey and/or the registration process can also request informationto define people that would be candidates for the user. For instance,whether the user is seeking individuals of a specific religious group,ethnic background or sexual orientation.

The survey 20 need not be constant and can change with time. Forinstance, as the matching service 14 finds that certain inquiries 22 areless effective at revealing relationship satisfaction, these inquiries22 can be dropped from the survey 20. Additionally, the matching servicecan add new questions to the survey to find out whether the newquestions add insight into relationship satisfaction.

As described above, the answers to the survey 20 are used to generate anempirical database. FIG. 3 is an example of an empirical database 24.The empirical database 24 includes a column of identifier fields 26 thateach identify a person who filled out the survey 20. Example identifiersinclude a person's name or other symbol associated with a particularperson. The empirical database 24 also includes a plurality of variablecolumns 28. Each variable column 28 is marked by a particular letterthat is associated with one of the inquiries 22 discussed above. Eachfield in a variable column 28 indicates a particular person's answer toa inquiry in the survey 20. Fields in the empirical database 24 can alsobe empty as results when certain inquiries 22 are dropped or added tothe survey 20. Empty fields can also result when a user chooses not toanswer one or more of the inquiries 22.

A correlation matrix 30 is constructed from the empirical database 24 inorder to illustrate the degree of correlation between the variables ofthe empirical database 24. An example of a correlation matrix 30 isillustrated in FIG. 4. Each field of the correlation matrix 30 shows thedegree of correlation between two of the variables. The degree ofcorrelation can vary from negative one to positive one. A value of oneindicates a high degree of correlation between the two variables. As aresult, the correlation between variable A and itself is 1. Thecorrelation matrix 30 is constructed from the empirical database 24. Asuitable program for generating the correlation matrix 30 is STATISTICAfrom Statsoft, Inc. of Tulsa Okla. The variables used to construct thecorrelation matrix 30 are selected from the variables in the empiricaldatabase 24 by the matching service 14. As a result, variables that areless relevant to the satisfaction of a couple can be removed from thecorrelation matrix 30.

The correlation matrix 30 is examined to identify combinations ofcorrelated variables that are commonly called factors. The factors areidentified in a statistical process known as factor analysis. Factoranalysis is a method of combining multiple variables into a singlefactor in order to reduce the total number of variables that must beconsidered. Hence, each factor is a function of one or more variables asillustrated in FIG. 5. For instance, the factors can be a weightedlinear combination of two or more varaibles. The factor analysis ispreferably performed to identify the minimum number of factors which areneed to account for the maximum percentage of the total variance presentin the original set of variables. A suitable factor analysis includes,but is not limited to, a principle component analysis with aneigenvalues greater than or equal to 1 criteria and a rotationalprocedure that is the biquartimax solution.

The factors are then used to generate a factor value database 32 such asthe database illustrated in FIG. 6. The factor value database 32 caninclude a column of identifier fields 26 and several columns of factorfields 34. Each field in a column of factor fields 34 lists the value ofa factor for a particular person. The people listed in the factor valuedatabase can include different people than the empirical database. Forinstance, as data in the empirical database becomes outdated it can bedropped from the factor value database.

The factor value database 32 also includes a column of individualsatisfaction index fields 36. The individual satisfaction indexindicates the level of satisfaction that a particular person who is apart of a couple has in that relationship. A suitable individualsatisfaction index is the Dyadic Adjustment Scale (DAS). The DAS is avalidated tool for assessing the level of satisfaction of a marriedperson in that person's marriage. The DAS for a particular person can begenerated from answers to inquiries 22 that are included in the survey20 discussed with respect to FIG. 1. Because the DAS can be determinedfor existing couples, the DAS is a useful individual satisfaction indexfor developing the data needed by the matching service 14 prior to thetime the matching service has enough users to generate statisticsconcerning the quality of matches that were made by the matchingservice. Other individual satisfaction indexes can be generated for usewith the present invention.

An individual satisfaction index can be generated from couples that arematched by the matching service 14. For instance, each matched couplecould be sent surveys 20 at various times after the match in order todetermine each person's level of satisfaction with the coupling. Theanswers to these surveys 20 could then be used to determine anindividual satisfaction index. A coupling index based on results ofmatching services 14 matches provides feedback concerning match results.Updating the methods of the present invention with this feedback allowsthe matching service to “learn” by taking into account the results ofprevious matches when making future matches. Other coupling indexes canalso be constructed for use with the methods of the present invention.

Individual satisfaction indexes determined by different methods can bescaled so they can be compared. Accordingly, an individual satisfactionindex generated from matching results can be compared with a DAS.Accordingly, the matching service 14 can convert a DAS based individualsatisfaction index to an individual satisfaction index derived frommatching results.

The factor value database 32 is used to approximate relationshipsbetween the individual satisfaction index and one or more of thefactors. This relationship is called an individual satisfactionestimator because the relationship can be used to approximate anindividual satisfaction index for an individual as will be described inmore detail below.

An individual satisfaction estimator can be determined for each matchgroup. A match group is a group of persons who may have differentfactors influence their satisfaction in a relationship. For instance,suitable match groups may include, straight men, straight women, gay menand gay women. A relationship for a particular match group is generatedusing only data for members of the particular match group.

A suitable method for approximating a relationship between theindividual satisfaction index and one or more of the factors includes,but is not limited to, performing a multiple linear regression andcorrelation analysis on the individual satisfaction indexes versus thefactor data. Software for performing the multiple linear regression andcorrelation analysis is available from STATISTICA from Statsoft, Inc. ofTulsa Okla. The linear regression is preferably a step-wise linearregression.

Multiple linear regression and correlation analysis is a preferredmethod for approximating the relationship because the differentialfactors that are minimally correlated to the couple satisfaction indexcan be removed from the relationship. Accordingly, the number of factorsincluded in the relationship are reduced. The factors included in therelationship are called selected satisfaction factors below.

FIG. 7 illustrates an example of generating a relationship between theindividual satisfaction index and one of the factors. For the purposesof illustration, the example is highly simplified to include a singlefactor. The individual satisfaction indexes for men are plotted versusthe value of a factor labeled F₁. The results of a step-wise linearregression performed on the plotted data is illustrated. These resultsare the approximated relationship between the individual satisfactionindex and the factor value.

Equation 1 is an example of an individual satisfaction estimatorgenerated using a multiple linear regression and correlation analysis.Each of the selected satisfaction factors is assigned a weight accordingto the degree of correlation between the value of the factor and theindividual satisfaction index. The higher the degree of correlationassociated with a particular factor, the higher the weight assigned tothat factor. The selected satisfaction factors are combined as shown inEquation 1 where C is the approximated individual satisfaction index,F_(i) is a selected satisfaction factor i and w_(i) is the weightassigned to F_(i).C=Σw_(i)F_(i)  Equation 1

As described above, the individual satisfaction estimator can be used todetermine an approximate individual satisfaction index for anindividual. The approximate individual satisfaction index is determinedby comparing the individual's survey answers to the individualsatisfaction estimator. For instance, the individual's answers can beused to calculate each of the selected satisfaction factors inEquation 1. Each of the calculated factors is substituted into Equation1 along with the appropriate weights to determine the approximatedindividual satisfaction index, C. As described above, the individualsatisfaction index is an indication of how satisfied an individual is ina relationship. Accordingly, the approximated individual satisfactionindex, C, that is determined for a person provides an indication of howsatisfied that person will be in the relationships that person formswith others.

The approximate individual satisfaction index can be used to classifyindividuals. For instance, individuals may be placed in an unlikely menclassification, an unlikely women classification, an average menclassification, an average woman classification, a good menclassification or a good woman classification. The unlikelyclassification may indicate that the user is unlikely to be happy in anyrelationship. The average classification indicates that the user has anaverage chance of forming satisfactory relationships and the goodclassification indicates that the user has an above average chance offorming satisfactory relationships. The classes can be broken downfurther to include personal information such as sexual orientation. Theuser can be placed in a particular classification based on whether hisindividual satisfaction index falls within a particular range associatedwith the classification. For instance, a man with low individualsatisfaction indexes can be placed in the unlikely men classificationand a woman with a high individual satisfaction index can be placed in agood woman classification. The matching service may choose not toprovide service to people who fall within particular classifications.For instance, the matching service may choose not to match people whofall within the unlikely classification.

A couple database 40 can also be generated from the factor valuedatabase 32. FIG. 8 illustrates an example of a couple database 40. Thecouple database 40 includes a column of couple identifier fields 42, acolumn of male individual satisfaction index fields 44A, a column offemale individual satisfaction index fields 44B and several columns ofdifferential factor fields. The fields in the column of malesatisfaction indexes list the individual satisfaction index for the maleof each couple and the fields in the column of female satisfactionindexes list the individual satisfaction index for the female of eachcouple. Although these column descriptions assume the couples include amale and female method, the couple database can be easily adapted toinclude couples of a single sex. The fields in the columns ofdifferential factor fields list the difference between the value of afactor for the couple. For instance, the fields in the column ofdifferential factor fields 46 labeled ΔF₁ can the list differencebetween the value of F₁ for the female of a couple and the value of F₁for the male of the couple.

The couple database 40 can be used to approximate relationships betweenthe individual satisfaction index and one or more of the differentialfactors. This relationship is called a couple satisfaction estimatorbecause it can be used to approximate the satisfaction that a personwould have in a relationship with a particular person. A couplesatisfaction estimator can be determined for each class that people areplaced into based on their individual satisfaction index or theirapproximate individual satisfaction index. A couple satisfactionestimator for a particular class is generated using only data formembers of the class. The matching service may have a class for peoplethat the matching service does not wish to match. Because people fallingwithin this class will not be matched, a couple satisfaction estimatordoes not need to be generated for this class.

A suitable method for approximating a relationship between theindividual satisfaction index and the one or more of the differentialfactors includes, but is not limited to, performing a multiple linearregression and correlation analysis on the individual satisfaction indexversus the differential factor data. Software for performing themultiple linear regression and correlation analysis is available fromSTATISTICA from Statsoft, Inc. of Tulsa Okla. The linear regression ispreferably a step-wise linear regression.

Multiple linear regression and correlation analysis is a preferredmethod for approximating the relationship because the differentialfactors that are minimally correlated to the couple satisfaction indexcan be removed from the relationship. Accordingly, the number ofdifferential factors included in the relationship can be reduced. Thefactors included in the relationship are called selected differentialfactors below.

FIG. 9 illustrates an example of generating a relationship between theindividual satisfaction index and one of the differential factors. Forthe purposes of illustration, the example is highly simplified toinclude a single differential factor. The individual satisfactionindexes for men in the average classification are plotted versus thevalue of a differential factor labeled ΔF₁. The results of a step-wiselinear regression performed on the plotted data is illustrated. Theseresults are the approximated relationship between the individualsatisfaction index and the differential factor value for men in theaverage class.

Equation 2 is an example of a couple satisfaction estimator generatedusing a multiple linear regression and correlation analysis. Each of theselected differential factors is assigned a weight according to thedegree of correlation between the value of the differential factor andthe individual satisfaction index. The higher the degree of correlationassociated with a particular differential factor, the higher the weightassigned to that differential factor. The selected differential factorsare combined as shown in Equation 2 where CI is the approximate couplesatisfaction index, F_(i) is a selected satisfaction factor i and w_(i)is the weight assigned to F_(i).CI=Σw_(i)ΔF_(i)  Equation 2

As described above, the couple satisfaction estimator can be used todetermine an approximate couple satisfaction index for a couple. Theapproximate couple satisfaction index is determined by comparing thecouple's survey answers to the couple satisfaction estimator. Forinstance, the couple's answers can be used to calculate each of theselected differential factors in Equation 2. Each of these differentialfactors is substituted into Equation 2 along with the appropriateweights to determine the approximate couple satisfaction index, CI. Theapproximate couple satisfaction index is an approximate value of thesatisfaction index that a particular person would have in a relationshipwith another person.

During the matching stage, the matching system 10 matches a useroperating a remote unit 16 with one or more candidates. The user fillsout a survey 20 at the remote unit 16. In one embodiment, the survey 20includes only the variables needed to calculate each of the selectedfactors and the selected differential factors. In another embodiment,the survey 20 includes the variables needed to calculate each of thefactors identified during the factor analysis. In yet anotherembodiment, the survey 20 includes more variables than are needed tocalculate the factors identified during the factor analysis.

The matching service 14 receives the survey 20 filled out by the userand the user's match group is identified. The individual satisfactionestimator associated with the identified match group is identified. Theuser's answers to the inquiries 22 are compared to the identifiedindividual satisfaction estimator to determine an approximate individualsatisfaction index for the user.

The user is then placed in a class based on the user's approximateindividual satisfaction index. As described above, users may be placedin an unlikely men or women classification, an average men or womenclassification or a good men or women classification.

The matching service 14 then selects candidates to be matched with theuser. The selected candidates fall within either the same or similarclass as the user. Alternatively, the candidates fall within a classthat is similar to the user but includes members of the opposite sex.For instance, if the user is heterosexual and fits within the good menclassification, the candidates fall within the good womenclassification.

The matching service identifies the couple satisfaction estimatorassociated with the user's classification and one of the identifiedcandidates is selected. The user's answers to the inquiries 22 and theselected candidate's answers to the questions are compared to theidentified couple satisfaction estimator to determine an approximatecouple satisfaction index for the user and the selected candidate. Asdiscussed above, the approximate couple satisfaction index approximatesthe satisfaction that the user will have in a relationship with theselected candidate. An approximate couple satisfaction index isgenerated for each identified candidate.

The matching service uses the approximate couple satisfaction index toidentify potential matches for the user. For instance, the matchingservice can select candidates who result in a couple satisfaction indexover a particular threshold as potential matches. Alternatively, somepre-determined number of candidates resulting in the highest couplesatisfaction indexes are identified as potential match candidates.

Additionally, the matching service can use a criteria based ondetermining a couple satisfaction index for both and a couplesatisfaction index for the candidate for each user and candidatecombination. For instance, for each combination of a user and acandidate, the matching service can identify the couple satisfactionpredictor associated with the class of the user and the couplesatisfaction predictor associate with the class of the candidate. Thesurvey answers for the user and the candidate can be compared to thecouple satisfaction predictor associated with the class of the user togenerate an approximate couple satisfaction index for the user. Thesurvey answers for the user and the candidate can also be compared tothe couple satisfaction predictor associated with the class of thecandidate to generate an approximate couple satisfaction index for thecandidate. Accordingly, the matching service will have approximated theuser's satisfaction in a relationship with a candidate and thecandidate's satisfaction in a relationship with a user. The matchingservice can combine these results to select the matches for the user.For instance, the approximate couple satisfaction index for thecandidate and the user can be added together and the candidates thatprovide the highest total will be selected as a potential match. Othercombinations of the approximate couple satisfaction index for thecandidate and the user can be used to select the potential matches. Forinstance, the approximate couple satisfaction index for the candidateand the user can be averaged and the difference between the approximatecouple satisfaction index for the candidate and the user can also bedetermined. The candidates that yield the high averages and lowdifferences can be selected as the potential matches.

During the communication stage, the matching service 14 providespreliminary information for each of the potential match candidates tothe user. The matching service 14 can also provide the user with severalcommunication levels from which to choose. Alternatively, the matchingservice can arrange the communication levels in a particular sequenceand require that the user and the candidate being in a particularcommunication level.

Each of the communication levels allows the parties to exchangeinformation in a different format. Examples of exchanging information atdifferent communication levels include exchanging answers to open-endedquestions provided by the matching service, exchanging items selectedfrom a list provided by the matching service, exchanging answers toopen-ended questions provided by the matching service and exchangingquestions and answers written by the user and/or the candidate.

The communication levels can be arranged in a preferred communicationlevel sequence. For instance, the communication levels can be sequencedso a user and a candidate proceed through the communication levels sothey are able to exchange increasingly personal information. Once thematching service has settled on a particular sequence, the matchingservice may require that a user and a candidate progress through thecommunication levels in sequence. However, the matching service canprovide the user and a candidate with the option of choosing when toprogress to the next communication level.

One embodiment of the matching service 14 allows the user and candidateto select which communication levels they use to communicate. As aresult, the user and candidate select the level on which they are mostcomfortable communicating and can move forward with forming arelationship by proceeding to a communication level that allows for theexchange of more personal information. Alternatively, a user andcandidate can back off of a relationship by proceeding to acommunication level that allows for a less personal exchange ofinformation.

When the user and the candidate use the communication service toexchange information they communicate the information to the matchingservice 14 which then forwards the information to its destination. Thematching service 14 can perform this exchange by forwarding an emailfrom one user to another user. The matching service 14 can replace eachusers email address with the user's username before forwarding thee-mail. As a result, the address of the sender remains confidential andis not available to the ultimate recipient. Accordingly, informationexchanged through the matching service 14 is confidential. Additionally,the matching service 14 can hold information that it receives from theuser until it has received a response from the candidate or vice versa.As a result, one person can not get the information from another personwithout making an even exchange.

The matching service 14 can facilitate an exchange of closed-endedquestions 22 by providing the user and the candidate with a list ofclosed-ended questions 22. An example of a closed-ended questionincludes the following.

If you were taken by your date to a party where you knew no one, howwould you respond?

a) Stay close to my date, letting he/she introduce me.

b) Find a spot at the back bar and relax alone.

c) Strike out on my own and make friends.

d) Ask if I could skip the event.

The user's answers are provided to the candidate and the candidate'sanswers are provided to the user.

The matching service 14 can facilitate an exchange of lists by providingboth the user and the candidate with the same or similar lists. The userand candidate can be directed to select whatever they want from the listor to select a pre-determined number of items from the list. Forinstance, the user and the candidate can be directed to select 10 itemsfrom the following list. The lists can be directed toward particularsubjects including, but not limited to, relationship issues, religiousissues, entertainment items, money and food. In one embodiment, the userand/or the candidate can select the subject matter for the list. Inanother embodiment, the user and the candidate must agree on the subjectmatter of the lists.

Examples of lists include, but are not limited to, a list of “musthaves” and/or a list of “can't stands.” Examples of must haves directedtoward relationship issues include the following.

I must feel deeply in love and attracted my partner.

I must have someone who is good at talking and listening.

I must have someone who is sharp and will keep me on my toes.

Examples of can't stands directed toward relationship issues include thefollowing.

I can't stand someone who is belittling or hateful to people.

I can't stand someone who has a chip on their shoulder.

I can't stand someone who sees material items as a matter ofsatisfaction.

The user's selections from the list are provided to the candidate andthe candidate's selections from the list are provided to the user. Onlythe items selected from the list can be provided to the other party orthe entire list with the selected items marked can be provided to theother party.

The matching service 14 can facilitate an exchange of one or moreopen-ended questions 22 by providing both the user and the candidatewith the same or similar open inquiries 22. The open-ended questions 22can be directed toward particular subjects including, but not limitedto, relationship issues, religious issues, entertainment items, moneyand food. In one embodiment, the user and/or the candidate can selectthe subject matter for the open-ended questions 22. In anotherembodiment, the user and the candidate must agree on the subject matterof the open-ended questions 22.

Examples of open-ended questions 22 directed toward relationship issuesinclude the following.

Besides love, what one trait have you noticed in couples that havemaintained a successful relationship for many years?

Looking back on your life of what are you most proud?

The user's answers are provided to the candidate and the candidate'sanswers are provided to the user.

In another communication level, the matching service 14 facilitates anexchange of inquiries 22 written by the user and/or by the candidate. Asdescribed above, the inquiries 22 are forded between the parties throughthe matching service 14. Accordingly, the matching service 14 can retainconfidentiality by removing personal information from an e-mail. Forinstance, the matching service 14 can replace an e-mail address with apersons user name. Although these inquiries 22 are written by the userand/or the candidate, the matching service 14 can provide lists ofexamples for guidance. For instance, the matching service 14 can providea list of inquiries 22 including the following inquiries 22.

What person in your life has been most inspirational and why?

Tell me about your closest friend. How long have you known them; andwhat do like best about them?

The user's answers are provided to the candidate and the candidate'sanswers are provided to the user.

Because this communication level allows communication between the userand the candidate with the matching service 14 serving as anintermediary that preserves confidentiality, the user and the candidatecan use this communication stage to communicate as would be done indirect e-mail communications. Hence, a user and candidate in thiscommunication stage need not stay exchanging inquiries 22. For instance,the user and the candidate can exchange their e-mail addresses, phonenumbers and/or set up a time to meet elsewhere.

In another communication level, the matching service 14 facilitates opencommunication between the user and/or by the candidate. For instance,the user can request that the matching service 14 make his/her contactinformation available to the candidate and/or the candidate can requestthat the matching service 14 make his/her contact information availableto the user. Suitable contact information includes, but is not limitedto, e-mail addresses, phone numbers and street addresses.

FIG. 10 illustrates an embodiment of a method of operating a matchingsystem 10. The method begins at start block 200. At process block 202,the matching service 14 prepares empirical data. An example of a methodfor preparing the empirical data is illustrated in FIG. 12. At processblock 204, the matching service 14 uses the prepared empirical data tomatch a user of the matching service 14 with one or more candidatesselected from a pool of candidates. An example of a method for matchingthe user with one or more candidates is illustrated in FIG. 13. Atprocess block 206, the matching service 14 provides communicationbetween the user and the one or more selected candidates. FIG. 16provides an example of a method of providing communication between theuser and the one or more selected candidates. The method terminates atend block 208.

FIG. 11 illustrates an example of a method of preparing empirical datafor matching a user with a candidate. The empirical data can be preparedbefore each user is to be matched with a candidate. Alternatively, theempirical data can be prepared periodically. For instance, the preparedempirical data can be used to match several users of the matchingservice 14 with candidates and then the empirical data can be preparedagain.

The method of preparing the empirical data begins at start block 210.The method can be started in response to a user using a remote unit 16to access the matching service 14, completing a survey 20 and requestinga list of potential matches. Alternatively, the method can be started inresponse to particular criteria such as passage of a particular amountof time or a particular number of users having been matched. At processblock 212 the empirical database 24 is updated. This database can beupdated to include information from a completed survey 20 submitted by auser who is requesting a list of potential matches. Updating thedatabase can also include removal of information from the database. Forinstance, outdated information can be extracted. Additionally,information can be extracted in order or to convert the database fromuse of a DAS to an individual satisfaction index which is the result ofmatches resulting from the matching service 14. Other databases can beupdated at this stage. For instance, data for generating an individualsatisfaction index for each member of a couple that was matched by thematching service can be incorporated into the databases. The resultingindividual satisfaction index can be listed in the factor valuedatabase.

At process block 214, the updated empirical database 24 is used togenerate an individual satisfaction estimator. At process block 216, theupdated empirical database 24 is used to generate a couple satisfactionestimator. The method terminates at end block 218.

FIG. 12 illustrates a method of matching a user of the system 10 withone or more candidates. The method starts at start block 220 when a usercompletes a survey 20 and requests a list of potentially matchingcandidates. At process block 222 the completed survey 20 is receivedfrom the user. The user preferably employs a remote unit 16 to transmitthe survey 20 to the matching service 14 although the survey 20 can bemailed or completed in person at the matching service 14.

At process block 224, the satisfaction that the user has inrelationships that the user forms with others is approximated. Thisapproximation can be made by determining an approximate individualsatisfaction index for the user. One method for determining theapproximate individual satisfaction index includes identifying the matchgroup to which the user belongs. The individual satisfaction estimatorassociated with the identified match group is then identified. Theuser's answers to at least a portion of the inquiries 22 on the survey20 are compared to the identified individual satisfaction estimator. Inone embodiment, comparing the user's answers to the identifiedindividual satisfaction estimator includes calculating the value of theselected factors from the answers that the user provided and thencomparing the calculated factors to the individual satisfactionestimator. At process block 226, the approximate individual satisfactionindex is used to classify the user.

At process block 228, the candidates that fall within the classificationof the user are identified. At process block 230, the satisfaction thatthe user would have in a relationship with each of the identifiedcandidates is approximated. This approximation can made by determiningan approximate couple satisfaction index for the user and a candidate.One method for determining the approximate couple satisfaction indexincludes comparing at least a portion of the answers provided by theuser and the candidate to the couple satisfaction estimator. In oneembodiment, comparing the answers provided by the user and the candidateto the couple satisfaction estimator includes calculating the selecteddifferential factors from the answers provided by the user and acandidate and comparing the selected differential factors to the couplesatisfaction estimator.

At process block 232, the approximated satisfaction that the user wouldhave in a relationship with each of the identified candidates are usedto select the candidates for a potential match with the user. Asdescribed above, selecting the candidates can also include approximatingthe satisfaction that each candidate would have in a relationship withthe user. The method then terminates at end block 234.

FIG. 13 illustrates a method of providing communication between the userand a candidate. As described above, one embodiment of the inventionincludes allowing the user and a candidate to select the communicationlevel on which they will communicate while another embodiment of theinvention requires the user and a candidate to progress through asequence of communication levels.

FIG. 13 illustrates providing communication between the user and acandidate when the matching service requires that the user and candidateproceed through a sequence of communication levels.

The method starts at start block 250. The user is notified of theselected candidates at process block 252. The preliminary informationfor each of the selected candidates is provided to the user are processblock 254. At determination block 256, a determination is made whetherthe user wishes to communicate with any of the selected candidates. Whenthe determination is positive, determination block 258 is accessed. Atdetermination block 258, a determination is made whether the candidateis interested in communicating with the user. This determination can bemade by providing a candidate with the user's preliminary information.The candidate can respond to the matching service 14 by indicatingwhether he/she would like to communicate with the user.

When it is determined that the candidate would like to communicate withthe user at determination block 258, process block 262 is accessed. Atprocess block 262, communication is provided between the user and acandidate at the first communication level of the sequence. As describedabove, providing communication can include forwarding communication fromone party to another and/or forwarding questions, lists, data or otherinformation from the matching service 14 to the user and/or thecandidate.

At determination block 264, a determination is made whether the userand/or the candidate would like to proceed to another communicationlevel. The matching service 14 can make this determination bytransmitting a communication to one or both parties asking whether theywould like to try a new communication level. One or both of the partiescan be presented with this option after proceeding to a certain point inthe current communication level. Alternatively, a communication beingforwarded from one party to another can be modified to include theoption of indicating a new communication level or the option can simplyaccompany the communication from one party to the other. When neitherparty indicates that they would like to communicate at the nextcommunication level, the determination is negative and the methodreturns to process block 262.

When one or both parties indicate that they would like to try the nextcommunication level, the determination at determination block 264 ispositive and the method proceeds to process block 266. At process block266, communication is provided between the user and a candidate at thenext communication level of the sequence. At determination block 270 adetermination is made whether the user and/or the candidate would liketo proceed to another communication level. The matching service 14 canmake this determination as described with respect to decision block 264.When the determination is positive, the method returns to process block268. When the determination is negative, the method proceeds to processblock 272 where the matching service continues to provide communicationat the current communication level.

When the determination at determination block 256 or determination block258 are negative, the method terminates at end block 268. Additionally,either party can indicate to the matching service 14 that they wish toterminate the communication at any time. When a party indicates thatthey wish to terminate the communication, the method ends at end block270.

The methods described above with respect to the data preparation stageand/or the matching stage can be used to train a neural network. Theneural network can be trained to receive data from a user's survey andto output a list of potentially matching candidates for that user. Asuitable neural network includes, but is not limited to, a principalcomponent analysis (PCA) neural network that includes a mixture ofunsupervised and supervised. The unsupervised segment of the network canperform the factor analysis. A PCA neural network converges very rapidlyand there are usually fewer factors extracted than there are inputs, sothe unsupervised segment provides a means of data reduction.

A simplified example of a supervised backpropogated neural network isillustrated in FIG. 14. The supervised backpropogated neural networkincludes a plurality of input units 300 that are each in communicationwith a hidden unit 302. Each hidden unit 302 is in communication with anoutput unit 304. Although a single layer of hidden units 302 isillustrated, the backpropogated neural network can include more than onelayer of hidden units 302. The supervised backpropogated neural networkcan be trained to randomly determine parameter values and carry outinput-to-output transformations for identifying matching candidates fora user.

The PCA data is applied to train the backpropagated neural network. Inthe supervised segment, the network performs the (linear or nonlinear)classification of the factors using a back propagation architecture thatcan randomly determine parameter values and carry out input-to-outputtransformations for actual problems. The correct final parameters areobtained by properly modifying the parameters in accordance with theerrors that the network identifies in the process. The use of backpropagation can include a delta rule network in which the one or morelayers of hidden units 302 are added. The network topology can beconstrained to be feed forward. For instance, the connections can beallowed from the input layer to the first hidden layer and from thefirst hidden layer to any subsequent hidden layers and then to theoutput layer. Multiple hidden layers can learn to recode the inputs toachieve the best estimation of output units 304.

The neural network can also include a Kohonen neural network so it canadapt in response to the inputs. The use of a Kohonen neural networkallows for self-organizational mapping and competitive learning. Inself-organizational mapping, the Kohonen neural network allows for theprojection of multidimensional points onto two dimensional networks. Incompetitive learning, the Kohonen neural network finds a pattern ofrelationships that is most similar to the input pattern. This results ina Kohonen clustering algorithm that takes a high dimensional input andclusters it but retains some topological ordering of the output. Thisclustering and dimensionality reduction is very useful as a furtherprocessing stage in which further neural networking data processing canbe accomplished and the identification of match candidates optimized.

Although the above description is largely directed toward matchingpeople in couples, the methods can be easily adapted to includerelationships with more than two people. Additionally, the methods canbe adapted to match people for purposes other than romanticrelationships. For instance, people who would be suitable for a businessrelationship can also be identified. Further, the methods need not belimited to people. For instance, the methods can be adapted for thematching of business establishments.

Other embodiments, combinations and modifications of this invention willoccur readily to those of ordinary skill in the art in view of theseteachings. Therefore, this invention is to be limited only by thefollowing claims, which include all such embodiments and modificationswhen viewed in conjunction with the above specification and accompanyingdrawings.

1. A method, performed by a computer, for operating a matching service,said method comprising: obtaining first survey data from non-candidatesurvey participants, said first survey data being responsive toinquiries into matters that are relevant to personal relationships withother people; using the first survey data to determine a set of one ormore factors associated with predicting satisfaction in a personalrelationship, including determining for each of the set of factors acorresponding function of one or more variables; maintaining a databaseof match candidates; gathering second survey data from a user candidate,said second survey data being responsive to inquiries into matters thatare relevant to the formation of personal relationships with otherpeople; and automatically identifying, based at least upon said set offactors and said second survey data, at least one of said matchcandidates for a personal relationship with said user candidate.
 2. Amethod according to claim 1, wherein said obtaining step obtains saidfirst survey data from individuals in an existing relationship.
 3. Amethod according to claim 1, wherein said obtaining step obtains saidfirst survey data from previously existing couples.
 4. A methodaccording to claim 1, wherein said first survey data includes datarelevant to existing relationships.
 5. A method, performed by acomputer, for operating a matching service, said method comprising:obtaining first survey data from people in currently existing personalrelationships, said first survey data being responsive to inquiries intomatters that are relevant to personal relationships with other people;using the first survey data to determine a set of one or more factorsassociated with predicting satisfaction in a personal relationship,including determining for each of the set of factors a correspondingfunction of one or more variables; maintaining a database of matchcandidates; gathering second survey data from a user candidate, saidsecond survey data being responsive to inquiries into matters that arerelevant to the formation of personal relationships with other people;and automatically identifying, based at least upon said set of factorsand said second survey data, at least one of said match candidates for apersonal relationship with said user candidate.
 6. A method according toclaim 5, wherein said obtaining step obtains said first survey data frommarried individuals.
 7. A method according to claim 6, wherein saidobtaining step obtains said first survey data from married couples.
 8. Amethod according to claim 5, wherein said first survey data includesdata relevant to said currently existing relationships.
 9. A methodaccording to claim 5, wherein said obtaining step obtains said firstsurvey data from non-candidate survey participants.
 10. A method,performed by a computer, for operating a matching service, said methodcomprising: processing first survey data from people in currentlyexisting personal relationships to identify a set of one or more factorsassociated with predicting satisfaction in a personal relationship,including determining for each of the set of factors a correspondingfunction of one or more variables; gathering second survey data from auser candidate, said second survey data being responsive to inquiriesinto matters that are relevant to the formation of personalrelationships with other people; and automatically estimating, inresponse to the set of one or more factors and said second survey data,personal relationship satisfaction between said user candidate and oneor more match candidates.
 11. A method according to claim 10, whereinsaid processing step processes first survey data obtained from marriedindividuals.
 12. A method according to claim 11, wherein said processingstep processes first survey data obtained from married couples.
 13. Amethod according to claim 10, wherein said first survey data isresponsive to inquiries into matters that are relevant to the formationof relationships with other people.
 14. A method according to claim 10,wherein said obtaining step obtains said first survey data fromnon-candidate survey participants.
 15. A system for operating a matchingservice, comprising: a database configured to maintain match candidates;and a processor configured to: obtain first survey data fromnon-candidate survey participants, said first survey data beingresponsive to inquiries into matters that are relevant to personalrelationships with other people; use the first survey data to determinea set of one or more factors associated with predicting satisfaction ina personal relationship, including determining for each of the set offactors a corresponding function of one or more variables; gather secondsurvey data from a user candidate, said second survey data beingresponsive to inquiries into matters that are relevant to the formationof personal relationships with other people; and automaticallyidentifying, based at least upon said set of factors and said secondsurvey data, at least one of said match candidates for a personalrelationship with said user candidate.
 16. A system according to claim15, wherein the processor is further configured to process said firstsurvey data to identify criteria related to successful relationships.17. A system according to claim 16, wherein the processor is configuredto process said first survey data, including identifying criteriarelated to successful current relationships.
 18. A system according toclaim 16, wherein the processor is configured to process said firstsurvey data, including identifying criteria related to successful pastrelationships.
 19. A system according to claim 15, wherein the processoris configured to obtain by obtaining said first survey data fromindividuals in an existing relationship.
 20. A system according to claim15, wherein said first survey data includes data relevant to previouslyexisting relationships.
 21. A system according to claim 15, wherein saidsecond survey data includes data relevant to a previous relationship ofsaid user candidate.
 22. A system for selecting matches for a user,comprising: a database configured to store: information associated withone or more people who are potential matches; and information associatedwith personal relationships obtained from one or more surveyparticipants, including at least one survey participant who is not oneof the people who are potential matches and who is not a user beingmatched; and a processor configured to: using the information obtainedfrom the one or more survey participants to determine a set of one ormore factors associated with predicting satisfaction in a personalrelationship, including determining for each of the set of factors acorresponding function of one or more variables; and automaticallyselecting matches, if any, for a personal relationship with the userbeing matched from the people who are potential matches based at leastin part on the set of factors.
 23. A system according to claim 22,wherein: the processor is further configured to processes theinformation associated with relationships to obtain criteria associatedwith successful relationships; and the information associated withrelationships used by the processor to select matches includes thecriteria associated with successful relationships.
 24. A systemaccording to claim 22, wherein: the processor is further configured toobtain information associated with relationships from the user beingmatched; and the processor is configured to select matches based furtherin part on the information obtained from the user being matched.
 25. Asystem according to claim 22, wherein: the processor is furtherconfigured to obtain information associated with relationships from theuser being matched, including information about past relationships theuser being matched has been in; and the processor is configured toselect matches based further in part on the information obtained fromthe user being matched.